N - mixture models by species

modelling N by site to get relative abundance

abundance by site will be used as a cov on predator occupancy

7 models evaluated, dot, jdt + jdtSQ, lure + jdt + jdtSQ


Species:      Chipmunk



Metadata Summary:

N_sites N_counts N_detections rep_period iterations burnin thin
127 221 129 7 days 120000 20000 10



Detections by Year:

Yr 2016 2017 2018 2019 2020
sites 19 31 19 32 26
detections 15 31 14 26 43
N.dot.model 10 16 7 8 22



WAIC

Models by WAIC:
model description WAIC N.total.est
fm7 counts 4.060804 127
fm5 jdt + jdtSq 830.680975 59
fm6 lure + jdt + jdtSq 831.757572 62
fm2 jdt 857.470979 61
fm4 lure + jdt 858.315210 67
fm3 lure 859.204048 60
fm1 dot 865.500876 63



Model summaries:



model: fm1
dot



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
p[1] NA 1486 0.052 0.046 0.01 0.09 0 0.9977
p[2] NA 4787 0.076 0.07 0.04 0.11 0 1.001
p[3] NA 4902 0.053 0.047 0.02 0.08 0 1.001
p[4] NA 7512 0.124 0.119 0.07 0.17 0 1.001
p[5] NA 4250 0.064 0.062 0.04 0.09 0 1.001
lambda[1] NA 162 1.122 0.566 0.22 1.65 0 1.0013
lambda[2] NA 5123 0.752 0.637 0.37 1.11 0 1.001
lambda[3] NA 3172 0.496 0.342 0.13 0.81 0 1.0009
lambda[4] NA 9210 0.271 0.22 0.10 0.42 0 1.001
lambda[5] NA 4293 0.991 0.867 0.51 1.44 0 1.001
N[66] NA 5684 1.201 err 1.00 2.00 err err
N[100] NA 10000 0.002 err 0.00 0.00 err err
N[81] NA 9382 1.024 err 1.00 1.00 err err
N[68] NA 4898 1.478 1 1.00 2.00 0 1.0001
N[33] NA 7970 1.143 err 1.00 2.00 err err

p[1]

p[2]

p[3]

p[4]

p[5]

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[66]

N[100]

N[81]

N[68]

N[33]







model: fm2
jdt



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha jdt 9017 0.206 0.198 0.05 0.38 0.13548 0.9789
alpha0 NA 4853 -2.666 -2.654 -2.91 -2.42 0 1.001
lambda[1] NA 9430 0.572 0.485 0.24 0.87 0 1.001
lambda[2] NA 8256 0.777 0.726 0.42 1.10 0 1.001
lambda[3] NA 10000 0.399 0.324 0.14 0.63 0 1.001
lambda[4] NA 8344 0.366 0.335 0.15 0.55 0 1.001
lambda[5] NA 7705 0.961 0.857 0.55 1.35 0 1.001
N[64] NA 10000 0.034 err 0.00 0.00 err err
N[27] NA 9541 2.016 2.002 1.00 3.00 0 1.0006
N[75] NA 10000 0.064 err 0.00 0.00 err err
N[30] NA 9529 1.903 2.002 1.00 3.00 0 1.0005
N[101] NA 9535 0.016 err 0.00 0.00 err err

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[64]

N[27]

N[75]

N[30]

N[101]

alpha relationship







model: fm3
lure



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha lure 9307 -0.119 -0.106 -0.31 0.05 0.60432 0.856
alpha0 NA 4900 -2.643 -2.64 -2.88 -2.39 0 1.001
lambda[1] NA 9201 0.575 0.496 0.24 0.88 0 1.001
lambda[2] NA 7998 0.746 0.693 0.41 1.05 0 1.001
lambda[3] NA 9341 0.388 0.333 0.14 0.62 0 1.001
lambda[4] NA 8568 0.368 0.325 0.16 0.56 0 1.001
lambda[5] NA 7748 0.960 0.895 0.54 1.36 0 1.001
N[9] NA 9611 1.133 err 1.00 2.00 err err
N[105] NA 8904 2.031 err 1.00 3.00 err err
N[115] NA 9512 0.089 err 0.00 0.00 err err
N[83] NA 10000 0.094 err 0.00 0.00 err err
N[42] NA 10000 0.271 err 0.00 1.00 err err

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[9]

N[105]

N[115]

N[83]

N[42]

alpha relationship







model: fm4
lure + jdt



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha[1] lureDays 5624 -0.298 -0.287 -0.50 -0.09 0.06692 0.9917
alpha[2] julianDt 6353 0.334 0.332 0.14 0.51 0.01151 0.9997
alpha0 NA 3381 -2.782 -2.758 -3.06 -2.51 0 1.001
lambda[1] NA 9381 0.529 0.451 0.23 0.82 0 1.001
lambda[2] NA 7768 0.750 0.712 0.42 1.08 0 1.001
lambda[3] NA 9556 0.410 0.362 0.15 0.65 0 1.001
lambda[4] NA 7727 0.382 0.32 0.16 0.58 0 1.001
lambda[5] NA 4577 1.228 1.118 0.68 1.78 0 1.001
N[58] NA 9630 0.040 err 0.00 0.00 err err
N[93] NA 10000 0.064 err 0.00 0.00 err err
N[71] NA 9154 0.019 err 0.00 0.00 err err
N[101] NA 9680 0.026 err 0.00 0.00 err err
N[99] NA 10000 0.034 err 0.00 0.00 err err

alpha[1]

alpha[2]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[58]

N[93]

N[71]

N[101]

N[99]







model: fm5
jdt + jdtSq



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha[1] julianDt 2780 -0.568 -0.553 -0.84 -0.31 0.00519 1.0001
alpha[2] julianDtSq 2761 0.891 0.912 0.63 1.15 0 1.001
alpha0 NA 4654 -2.746 -2.737 -3.00 -2.49 0 1.001
lambda[1] NA 7317 0.701 0.577 0.29 1.06 0 1.001
lambda[2] NA 8674 0.644 0.624 0.36 0.93 0 1.001
lambda[3] NA 8596 0.422 0.35 0.15 0.67 0 1.001
lambda[4] NA 9160 0.331 0.285 0.15 0.51 0 1.001
lambda[5] NA 7130 0.988 0.923 0.56 1.38 0 1.001
N[41] NA 10000 0.055 err 0.00 0.00 err err
N[42] NA 10000 0.255 err 0.00 1.00 err err
N[4] NA 9608 0.260 err 0.00 1.00 err err
N[37] NA 10000 1.140 err 1.00 2.00 err err
N[49] NA 9635 0.040 err 0.00 0.00 err err

alpha[1]

alpha[2]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[41]

N[42]

N[4]

N[37]

N[49]

julian date relationship







model: fm6
lure + jdt + jdtSq



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha[1] lureDays 5327 -0.211 -0.208 -0.41 -0.01 0.26016 0.9544
alpha[2] julianDt 2609 -0.431 -0.454 -0.72 -0.14 0.06676 0.991
alpha[3] julianDtSq 2765 0.854 0.835 0.60 1.12 0 1.001
alpha0 NA 3934 -2.819 -2.823 -3.08 -2.54 0 1.001
lambda[1] NA 7882 0.635 0.545 0.27 0.97 0 1.001
lambda[2] NA 8333 0.631 0.582 0.34 0.90 0 1.001
lambda[3] NA 8832 0.423 0.351 0.15 0.67 0 1.001
lambda[4] NA 9285 0.340 0.292 0.14 0.51 0 1.001
lambda[5] NA 5369 1.158 1.056 0.64 1.67 0 1.001
N[112] NA 8911 0.214 err 0.00 1.00 err err
N[79] NA 10000 1.078 err 1.00 1.00 err err
N[87] NA 10000 1.676 1 1.00 2.00 0 1.0004
N[50] NA 9679 0.038 err 0.00 0.00 err err
N[55] NA 10000 0.053 err 0.00 0.00 err err

alpha[1]

alpha[2]

alpha[3]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[112]

N[79]

N[87]

N[50]

N[55]







model: fm7
counts



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha counts 8949 6.936 6.22 4.88 8.89 0 1.001
alpha0 NA 10220 -7.500 -7.058 -9.12 -5.89 0 1.001
lambda[1] NA 10000 0.986 0.861 0.44 1.50 0 1.001
lambda[2] NA 9384 0.983 0.907 0.55 1.40 0 1.001
lambda[3] NA 8756 0.970 0.792 0.34 1.53 0 1.0009
lambda[4] NA 6875 0.961 0.853 0.39 1.50 0 1.001
lambda[5] NA 10000 0.986 0.932 0.57 1.38 0 1.001
N[103] NA 0 1.000 err 1.00 1.00 err err
N[76] NA 9245 0.939 0 0.00 2.00 1 err
N[27] NA 0 1.000 err 1.00 1.00 err err
N[96] NA 9341 0.940 0 0.00 2.00 1 err
N[58] NA 9344 0.950 0 0.00 2.00 1 err

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[103]

## Warning in cor(X, use = "pairwise.complete.obs"): the standard deviation is zero
## Warning: Removed 50 rows containing missing values (geom_bar).

N[76]

N[27]

## Warning in cor(X, use = "pairwise.complete.obs"): the standard deviation is zero
## Warning: Removed 50 rows containing missing values (geom_bar).

N[96]

N[58]

alpha relationship